Presentation
My expertise includes building robust web scraping systems using Python (Requests, BeautifulSoup, Selenium), handling dynamic content, anti-bot considerations, and large-scale data extraction. I focus on reliability, maintainability, and clean output formats (CSV, JSON, Excel, database ingestion).
In data engineering workflows, I develop ETL/ELT pipelines to extract, clean, transform, and load data into SQL and NoSQL databases. I work with relational databases (PostgreSQL, MySQL) as well as NoSQL systems (MongoDB), ensuring optimized schema design and efficient querying.
I also build automated Python scripts for recurring tasks, data synchronization, API integrations, and business process automation. I design REST APIs for data exposure and integration between systems, and I define KPIs to monitor performance and business metrics.
My technical stack includes:
Python (automation, scraping, data processing)
SQL & NoSQL databases
ETL / ELT pipeline design
REST API development
Docker for containerization
ELK Stack (Elasticsearch, Logstash, Kibana) for monitoring and logging
Prefect for workflow orchestration
Data validation and cleaning pipelines
I prioritize:
Clean, maintainable code
Scalable architectures
Clear documentation
Reliable delivery and communication
I am available for:
Web scraping & data extraction projects
Data pipeline design and optimization
Database design and query optimization
Automation systems
API development
Monitoring and KPI implementation
